On social laws for artificial agent societies: off-line design
Artificial Intelligence - Special volume on computational research on interaction and agency, part 2
Designing organizations for computational agents
Simulating organizations
An organizational ontology for enterprise modeling
Simulating organizations
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Multi-agent reward analysis for learning in noisy domains
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Autonomous Agents and Multi-Agent Systems
Formalizing organizational constraints: a semantic approach
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Organizational design principles and techniques for decision-theoretic agents
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Decentralized multi-robot cooperation with auctioned POMDPs
International Journal of Robotics Research
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Despite a large body of research on integrating organizational concepts into cooperative multiagent systems, a formal understanding of how organizations can influence agents' decisions remains elusive. This paper works toward such an understanding by beginning with a model of agent decision making based on decision-theoretic principles, and then examining the possible routes that organizational influences can take to affect that model. We show that alternative avenues of applying influences correspond to different prior notions of organizational control, and empirically demonstrate the impact that each can have on the quality and overhead of coordinated behavior. To do so, we must define the agents' baseline behavior (without a designed organization), and we present a methodology for initializing agents' models to comprise what amounts to an "uninformed" organization. Finally, we show how the specification of organizational influences in terms of components of a decision-theoretic agent creates opportunities for agents to compare actual events with predictions implied in the models, such that agents can reason about whether to change organizations. We demonstrate that this capability to question and change organizations can be valuable if used judiciously.